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Realistic face animation for speech

Abstract

Realistic face animation is especially hard as we are all experts in the
perception and interpretation of face dynamics. One approach is to simulate
facial anatomy. Alternatively, animation can be based on first observing the
visible 3D dynamics, extracting the basic modes, and putting these together
according to the required performance. This is the strategy followed by the
paper, which focuses on speech. The approach follows a kind of bootstrap
procedure.
First, 3D shape statistics are learned from a talking face with a relatively
small number
of markers. A 3D reconstruction is produced at temporal intervals of 1/25
seconds. A
topological mask of the lower half of the face is fitted to the motion.
Principal component analysis (PCA) of the mask shapes reduces
the dimension of the mask shape space. The result is two-fold. On the one
hand, the
face can be animated, in our case it can be made to speak new sentences. On
the other hand, face dynamics can be tracked in 3D without markers for
performance
capture.